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Unleash the Power of Large Language Models Using LangChain

Discover how to leverage LangChain through our Langchain course for the development of LLM-powered applications. Learn about prompt templates, chains, memory types, and tools to build AI applications.

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Adaptive Learning

AI-POWERED

Explanations

Adaptive Learning

This course includes

14 Lessons

20 Playgrounds

Course Overview

What You'll Learn

Course Content

Recommendations

Course Overview

Unlock the potential of large language models (LLMs) with our beginner-friendly LangChain course for developers. Founded in 2022 by Harrison Chase, LangChain has revolutionized GenAI app development. This interactive LangChain course integrates LLMs into AI applications, enabling developers to create smart AI solutions. Enhance your expertise in LLM application development and LangChain development. Explore LangChain’s core components, including prompt templates, chains, and memory types, essential for aut...Show More

Unlock the potential of large language models (LLMs) with our beginner-friendly LangChain course for developers. Founded in 2022...Show More

What You'll Learn

A comprehensive understanding of LangChain and its capabilities for AI application development

The ability to build robust GenAI apps and automate workflows using LangChain

Hands-on experience implementing a chatbot that responds to queries in multiple languages using the router chain in LangChain

The ability to utilize retrieval-augmented generation for efficient question-answering and information retrieval

The ability to explore LangGraph basics to create dynamic multi-agent systems for adaptable AI workflows

A comprehensive understanding of LangChain and its capabilities for AI application development

Course Content

Introduction to LangChain

3 Lessons

Get familiar with leveraging LangChain and large language models for GenAI solutions.

What is a Language Model?

What Is LangChain and Why Does It Matter?

Use Cases of LangChain

Exploring LangChain

5 Lessons

Work your way through LangChain's chat models, prompt templates, output parsers, runnables, tools, and vector stores.

Chat Models and Prompt Templates in LangChain

Parsing Outputs with LangChain

Runnables and LCEL

Tools in LangChain

Embeddings and Vector Stores in LangChain

LangGraph Basics

5 Lessons

Explore LangGraph's dynamic multi-agent systems for adaptable AI workflows. Understand the main components of LangGraph, and how to use them.

What is LangGraph?

What Are the Main Components of LangGraph?

Why Traditional Chains Fall Short?

How To Create A Routing System?

Quiz: Introduction to LangGraph

Wrapping Up

1 Lessons

Take a closer look at integrating LangChain with LLMs, dynamic agents, and future possibilities.

Conclusion

Query CSV Files with Natural Language Using LangChain and Panel

Project

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Frequently Asked Questions

What is LangChain?

LangChain is an open-source framework designed to empower developers in LLM application development by integrating large language models (LLMs) like OpenAI’s GPT-3.5 and GPT-4 with external tools and data sources. Founded in 2021 by Harrison Chase, LangChain revolutionizes how developers build GenAI applications by enabling the creation of smart, scalable AI solutions. With LangChain, you can connect language models with tools and data, automate workflows, and build powerful AI applications that leverage natural language processing (NLP) capabilities.

What prerequisites are needed before learning LangChain?

Before enrolling in our LangChain beginner course, it’s recommended to have a foundational understanding of Python programming and basic concepts in machine learning. Familiarity with large language models (LLMs) and AI application development will enhance your learning experience. However, the course is designed to accommodate both beginners and experienced developers. By starting with fundamental topics like prompt templates and chains, you’ll gradually build the skills necessary to learn LangChain effectively and apply them to build powerful AI applications. No prior experience with LangChain is required, making it accessible for anyone interested in advancing their AI development capabilities.

How does LangGraph complement LangChain in AI applications?

LangGraph enhances LangChain application development by providing a framework for building dynamic multi-agent systems. While LangChain focuses on integrating LLMs into AI applications, LangGraph basics enable developers to create robust routing systems and optimize AI workflows. This combination allows for precise control and adaptability in AI solutions, ensuring applications remain effective across diverse scenarios. By learning to integrate LangChain with other AI tools through LangGraph, you can develop sophisticated GenAI apps that automate complex tasks, manage conversational contexts, and handle multi-agent interactions seamlessly, building powerful applications with LangChain.

Is LangChain free?

LangChain is a free, open-source framework that allows developers to develop LLM applications and build powerful AI applications without licensing fees. As an open-source tool, LangChain provides access to essential components like prompt templates, chains, and memory types, making it ideal for beginners and experienced developers.

Is LangChain free?